Quantitative Researcher - Equities Monetization - Selby Jennings

Jobs via eFinancialCareers
US
Remote

Why this role

Pace
Fast Paced
The role is likely fast-paced, given the need to work with large datasets and the high visibility of the team within the firm, which suggests a dynamic and responsive work environment.
Collaboration
High
Collaboration is a key aspect of the role, as the Quantitative Researcher will work in a team of academics and industry veterans, contributing to a collaborative research agenda.
Autonomy
Medium
While the role involves teamwork, it also requires a high level of autonomy, as the researcher must independently develop and test new strategies, demonstrating strong self-motivation and initiative.
Decision Impact
Team
Decisions made by the Quantitative Researcher can have a significant impact on the firm's profitability, as the team's work directly influences the firm's PnL.
Role Level
Team Lead
The role is highly complex, requiring a deep understanding of statistical methods, portfolio construction, and the ability to work with large, noisy datasets.

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • high impact research
  • alpha signal combination
  • portfolio optimization
Typical background
exceptional academicsindustry veterans

Transferable backgrounds

  • Coming from Quantitative Analyst at a financial institution
    Statistical analysis · Python programming
    The background in quantitative analysis and Python programming provides a strong foundation for the role's requirements.
  • Coming from Data Scientist at a tech company
    Data handling · Machine learning
    Experience in handling large datasets and applying machine learning techniques can be directly applied to the role's focus on signal construction and optimization.

Skills & requirements

Required

StatisticsPortfolio Construction TechniquesPython CodingData AnalysisSTEM Degree

Preferred

Market Impact UnderstandingAlpha Signal CombinationPortfolio Optimization

Stack & domain

PythonStatisticsPortfolio Construction TechniquesMarket ImpactCollaborationCommunicationQuantitative Hedge FundEquities Business

About the role

This role involves working closely with a team of experts to develop and optimize investment strategies in the equities market, requiring a deep understanding of statistical analysis and coding skills, particularly in Python. Ideal candidates are those who can handle large, complex datasets and have a proven track record in quantitative research.

Original posting from Jobs via eFinancialCareers via LinkedIn

A long-standing, top-tier Quantitative Hedge Fund in NYC is looking for a Monetization Quant Researcher to join their equities business. The incoming QR will work in a collaborative team comprised of exceptional academics and industry veterans to spearhead a versatile research agenda comprised of alpha signal combination, portfolio optimization, signal construction and alpha/portfolio allocations.

The overall team commands high visibility within the firm given their impact on overall PnL. While the fund prioritizes exceptional technical capabilities and a demonstrated track-record in high impact research, culture remains one of their most key assets. The ideal candidate for the role will have:

  • Deep understanding of statistics and portfolio construction techniques.
  • Well versed in market impact and ways to consider this when deploying high capacity strategies in equity markets.
  • Exceptional Python coding, as well as associated packages for data
  • Ability to work with large, noisy datasets
  • STEM degree (MS or PhD strongly preferred)

Source: Jobs via eFinancialCareers careers (LinkedIn)

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